Remove CenterCrop from Classification test pipeline and editing missing docs link (#2375)

* Fix missing link for docs and removing centercrop for classification data pipeline

* Revert the test threshold

Author: sungmanc

docs/source/guide/explanation/algorithms/segmentation/semantic_segmentation.rst

@@ -42,7 +42,7 @@ Dataset Format
 
 For the dataset handling inside OpenVINO™ Training Extensions, we use `Dataset Management Framework (Datumaro) <https://github.com/openvinotoolkit/datumaro>`_.
 
-At this end we support `Common Semantic Segmentation <https://openvinotoolkit.github.io/datumaro/docs/formats/common_semantic_segmentation/>`_ data format.
+At this end we support `Common Semantic Segmentation <https://github.com/openvinotoolkit/datumaro/blob/develop/docs/source/docs/data-formats/formats/common_semantic_segmentation.md>`_ data format.
 If you organized supported dataset format, starting training will be very simple. We just need to pass a path to the root folder and desired model template to start training:
 
 .. code-block::
@@ -278,4 +278,4 @@ It can be launched only with supervised (incremental) training type.
 .. Incremental Learning
 .. ********************
 
-.. To be added soon
+.. To be added soon

src/otx/algorithms/classification/configs/base/data/data_pipeline.py

@@ -20,7 +20,7 @@
 __resize_target_size = 224
 
 __train_pipeline = [
-    dict(type="RandomResizedCrop", size=224, efficientnet_style=True),
+    dict(type="RandomResizedCrop", size=__resize_target_size, efficientnet_style=True),
     dict(type="RandomFlip", flip_prob=0.5, direction="horizontal"),
     dict(type="Normalize", **__img_norm_cfg),
     dict(type="ImageToTensor", keys=["img"]),
@@ -29,8 +29,7 @@
 ]
 
 __test_pipeline = [
-    dict(type="Resize", size=(256, -1)),
-    dict(type="CenterCrop", crop_size=224),
+    dict(type="Resize", size=__resize_target_size),
     dict(type="Normalize", **__img_norm_cfg),
     dict(type="ImageToTensor", keys=["img"]),
     dict(type="Collect", keys=["img"]),

tests/e2e/cli/classification/test_classification.py

@@ -180,8 +180,7 @@ def test_otx_explain_openvino(self, template, tmp_dir_path):
     @pytest.mark.parametrize("half_precision", [True, False])
     def test_otx_eval_openvino(self, template, tmp_dir_path, half_precision):
         tmp_dir_path = tmp_dir_path / "multi_class_cls"
-        # FIXME [Jaeguk] Revert threshold to 0.2 when model api supports resize and centercrop.
-        otx_eval_openvino_testing(template, tmp_dir_path, otx_dir, args, threshold=0.5, half_precision=half_precision)
+        otx_eval_openvino_testing(template, tmp_dir_path, otx_dir, args, threshold=0.2, half_precision=half_precision)
 
     @e2e_pytest_component
     @pytest.mark.skipif(TT_STABILITY_TESTS, reason="This is TT_STABILITY_TESTS")